ArticleChemical science2020
Evaluating and clustering retrosynthesis pathways with learned strategy.
Article in Chemical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- TridentSynth: a webtool for the retrosynthesis of molecules using chimeric type I polyketide synthases and chemoenzymatic pathways.Nucleic acids research · 2026Article
- A Return to the Logic-First Spirit of Corey's Retrosynthetic Analysis, Now Implemented in Modern Data-Driven CASP.ACS central science · 2026Article
- Higher-Level Strategies for Computer-Aided Retrosynthesis.ACS central science · 2026Article
- NOCTIS: open-source toolkit that turns reaction data into actionable graph networks.Journal of cheminformatics · 2025Article
- ASKCOS: Open-Source, Data-Driven Synthesis Planning.Accounts of chemical research · 2025Article
- Generating diversity and securing completeness in algorithmic retrosynthesis.Journal of cheminformatics · 2025Article
- Improving route development using convergent retrosynthesis planning.Journal of cheminformatics · 2025Article
- Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning.Beilstein journal of organic chemistry · 2025Review
- Molecular complexity as a driving force for the advancement of organic synthesis.Nature reviews. Chemistry · 2024Review
- Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review.ACS synthetic biology · 2024Article
- Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions.Journal of cheminformatics · 2024Article
- Machine learning-guided strategies for reaction conditions design and optimization.Beilstein journal of organic chemistry · 2024Review
- Machine Learning Methods for Small Data Challenges in Molecular Science.Chemical reviews · 2023Review
- A field guide to flow chemistry for synthetic organic chemists.Chemical science · 2023Review
- LinChemIn: SynGraph-a data model and a toolkit to analyze and compare synthetic routes.Journal of cheminformatics · 2023Article
- Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery.Chemical science · 2023Review
- Generic Interpretable Reaction Condition Predictions with Open Reaction Condition Datasets and Unsupervised Learning of Reaction Center.Research (Washington, D.C.) · 2023Article
- Cheminformatics and artificial intelligence for accelerating agrochemical discovery.Frontiers in chemistry · 2023Review
- Exploring Optimal Reaction Conditions Guided by Graph Neural Networks and Bayesian Optimization.ACS omega · 2022Article
- An all-round AI-Chemist with a scientific mind.National science review · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With recent advances in the computer-aided synthesis planning (CASP) powered by data science and machine learning, modern CASP programs can rapidly identify thousands of potential pathways for a given target molecule. However, the lack of a holistic pathway evaluation mechanism makes it challenging to systematically prioritize strategic pathways except for using some simple heuristics. Herein, we introduce a data-driven approach to evaluate the relative strategic levels of retrosynthesis pathways using a dynamic tree-structured long short-term memory (tree-LSTM) model. We first curated a retrosynthesis pathway database, containing 238k patent-extracted pathways along with ∼55 M artificial pathways generated from an open-source CASP program, ASKCOS. The tree-LSTM model was trained to differentiate patent-extracted and artificial pathways with the same target molecule in order to learn the strategic relationship among single-step reactions within the patent-extracted pathways. The model achieved a top-1 ranking accuracy of 79.1% to recognize patent-extracted pathways. In addition, the trained tree-LSTM model learned to encode pathway-level information into a representative latent vector, which can facilitate clustering similar pathways to help illustrate strategically diverse pathways generated from CASP programs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.